Optimal planning of Cross-regional hydrogen energy storage systems considering the uncertainty

Abstract

The cross-regional consumption of renewable energy can effectively solve the problem of the uneven spatial distribution of renewable energy. To explore the application of hydrogen energy storage systems (HESS) for cross-regional consumption of renewable energy, optimal planning of cross-regional HESS considering the uncertainty is researched in this study. Firstly, a two-layer planning model is proposed to consider investment and operation costs. The upper layer of the model aims to determine a feasible planning strategy for HESS based on existing conditions. The purpose of the lower layer is then to determine the optimal scheduling strategy and minimum operating cost of the system considering uncertainty based on distributionally robust optimization. Furthermore, the solution method that combines the modified Backtracking Search Algorithm (MBSA) and Yalmip/Cplex is utilized to determine the optimal placement and sizing of the HESS. Finally, the simulation experiment is performed with the case of Southwest China to verify the effectiveness of the proposed planning model and corresponding solution method. The simulation results show that the MBSA has a better convergence speed and stronger global search capability performance than the traditional BSA. MBSA converges at 44th, which is quicker than the 60th of BSA; the optimal objective value obtained by MBSA is $1,038,929,953.66, which is better than that of BSA of $1,051,512,303.18. In addition, the resulting HESS planning scheme can effectively reduce the network loss of the system, reduce the peak-to-valley load difference, and improve renewable energy consumption. Specifically, the system network loss is reduced from 1.56 MWh to 1.47 MWh, the peak-to-valley difference is reduced from 245.61 MW to 225.88 WM, and the total renewable energy consumption of four typical days is increased from 6582.07 MW to 7626.03 MW.